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%Turtlebot SLAM\hfill \\ \Large{Project MAI 1 2012-2013} \\ Group 3\\ \vspace{-.5\baselineskip}\rule{\linewidth}{1pt}}

\title{\Huge{Turtlebot SLAM} \\ \Large{ Group 3}}
\author{Murtadha Alqurqush\\Cristian Calmuschi\\Andreas Hamacher\\Gergely Kosztolányi\\Yannick Thimister}
\date{Maastricht \today}


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\begin{document}


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\fancyhead[LO,RE]{\sffamily Maastricht University}
\fancyhead[RO,LE]{\sffamily Project 1 MAI}
\fancyfoot[LO,RE]{\sffamily Department of Knowledge Engineering}
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\tableofcontents

\newpage


\section{Introduction}
Introduction including research questions etc.

\subsection{Research Questions}
\begin{itemize}
	\item \textbf{Phase 1:} How to create an efficient and accurate exploration algorithm for a mobile robot?
	\item \textbf{Phase 2:} How to create an as accurate as possible SLAM algorithm that can run in real-time?
	\item \textbf{Phase 3:} How to incorporate the algorithms in a real-world environment using a Turtlebot?
\end{itemize}

\section{Turtlebot}
Explanation of the turtlebot and its features/sensors
		\begin{itemize}
			\item Mobile robot
			\item Microsoft Kinect
			\item Laser range sensor
		\end{itemize}

\section{Robot Operating System}
Explain ROS and the general structure of the project program
		\begin{itemize}
		\item Nodes
			\item Messages
			\item Services
			\item Topics
		\end{itemize}

\section{Exploration}
Section about exploration task and frontier detection etc.
\begin{itemize}
	\item Good exploration strategy
	\begin{itemize}
		\item Accuracy
		\item Efficiency
	\end{itemize}
	
% idea of exploration:
\includegraphics[width=0.25\paperwidth]{images/step1.png}
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\includegraphics[width=0.25\paperwidth]{images/step3.png}
\begin{itemize}
	\item Left: Initial Localization, Mapping and frontier detection
	\item Middle: Exploration by navigating to a selected frontier
	\item Right: Further exploration based on the given strategie
\end{itemize}

\subsection{Occupancy Grid Map}
	\begin{itemize}
	\item Goal: Estimate the posterior probability over maps given the data $p(m | z, x) $
	\item Map as grid over the continuous space
	\item Each grid contains probability
		
		\center
		\includegraphics[width = 100pt]{images/occGridMap.png}
\end{itemize}
	\item Frontier-Detection algorithm
	\item Navigation
\end{itemize}
\subsection{Frontier Detection}
\begin{itemize}
	\item Frontiers: regions between open space en unexplored space
	\item Create evidence grid
	\item Label frontier cells
	\item Create frontiers
	\item Find centroid
	\item Wavefront detection
\end{itemize}

\section{Simultaneous Localization and Mapping}
Section about the SLAM algorithms
\subsection{Localization}
\begin{itemize}
	\item Sensor data perceive landmarks and walls
	\item Odometry data provides estimate of the robot's position
	\item Main part is an Extended Kalman Filter
	\begin{itemize}
			\item Update belief based on observations of features/landmarks
			\item Landmarks are features in the environment that are distinguishable
			\item Only re-observed landmarks are used to update
	\end{itemize}
\end{itemize}
\subsection{Mapping}
\subsection{Graph Based SLAM}

\section{Experiments and Results}
\subsection{Efficiency}
	\begin{itemize}
		\item How long does it take to explore the entire map or \\ when is the last frontier explored
		\item Comparing Strategies on fontier selection. \\ Distance vs. knowledge gain
	\end{itemize}
\subsection{Accuracy}
	\begin{itemize}
	    \item Increase of accuracy vs. measurement time.
		\item How accurate is the found map in comparison to the real map?
		\item Evaluation by visual comparison.
	\end{itemize}

\section{Conclusions}

\section{Discussion}
%just reference dummies
\cite{THRUNMAPPINGSURVEY}

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